Cross-link assisted spatial proteomics to map sub-organelle proteomes and membrane protein topologies.

The functions of cellular organelles and sub-compartments depend on their protein content, which can be characterized by spatial proteomics approaches. However, many spatial proteomics methods are limited in their ability to resolve organellar sub-compartments, profile multiple sub-compartments in parallel, and/or characterize membrane-associated proteomes. Here, we develop a cross-link assisted spatial proteomics (CLASP) strategy that addresses these shortcomings. Using human mitochondria as a model system, we show that CLASP can elucidate spatial proteomes of all mitochondrial sub-compartments and provide topological insight into the mitochondrial membrane proteome. Biochemical and imaging-based follow-up studies confirm that CLASP allows discovering mitochondria-associated proteins and revising previous protein sub-compartment localization and membrane topology data. We also validate the CLASP concept in synaptic vesicles, demonstrating its applicability to different sub-cellular compartments. This study extends the scope of cross-linking mass spectrometry beyond protein structure and interaction analysis towards spatial proteomics, and establishes a method for concomitant profiling of sub-organelle and membrane proteomes.

Extensive protein pyrophosphorylation revealed in human cell lines.

Reversible protein phosphorylation is a central signaling mechanism in eukaryotes. Although mass-spectrometry-based phosphoproteomics has become routine, identification of non-canonical phosphorylation has remained a challenge. Here we report a tailored workflow to detect and reliably assign protein pyrophosphorylation in two human cell lines, providing, to our knowledge, the first direct evidence of endogenous protein pyrophosphorylation. We manually validated 148 pyrophosphosites across 71 human proteins, the most heavily pyrophosphorylated of which were the nucleolar proteins NOLC1 and TCOF1. Detection was consistent with previous biochemical evidence relating the installation of the modification to inositol pyrophosphates (PP-InsPs). When the biosynthesis of PP-InsPs was perturbed, proteins expressed in this background exhibited no signs of pyrophosphorylation. Disruption of PP-InsP biosynthesis also significantly reduced rDNA transcription, potentially by lowering pyrophosphorylation on regulatory proteins NOLC1, TCOF1 and UBF1. Overall, protein pyrophosphorylation emerges as an archetype of non-canonical phosphorylation and should be considered in future phosphoproteomic analyses.

RawVegetable 2.0: Refining XL-MS Data Acquisition through Enhanced Quality Control.

We present RawVegetable 2.0, a software tailored for assessing mass spectrometry data quality and fine-tuned for cross-linking mass spectrometry (XL-MS) applications. Building upon the capabilities of its predecessor, RawVegetable 2.0 introduces four main modules, each providing distinct and new functionalities: 1) Pair Finder, which identifies ion doublets characteristic of cleavable cross-linking experiments; 2) Diagnostic Peak Finder, which locates potential reporter ions associated with a specific cross-linker; 3) Precursor Signal Ratio, which computes the ratio between precursor intensity and the total signal in an MS/MS scan; and 4) Xrea, which evaluates spectral quality by analyzing the heterogeneity of peak intensities within a spectrum. These modules collectively streamline the process of optimizing mass spectrometry data acquisition for both Proteomics and XL-MS experiments. RawVegetable 2.0, along with a comprehensive tutorial is freely accessible for academic use at: http://patternlabforproteomics.org/rawvegetable2.

The potential of cross-linking mass spectrometry in the development of protein-protein interaction modulators.

Cross-linking mass spectrometry (XL-MS) can provide a wealth of information on endogenous protein-protein interaction (PPI) networks and protein binding interfaces. These features make XL-MS an attractive tool to support the development of PPI-targeting drugs. Though not yet widely used, applications of XL-MS to drug characterization are beginning to emerge. Here, we compare XL-MS to established structural proteomics methods in drug research, discuss the current state and remaining challenges of XL-MS technology, and provide a perspective on the future role XL-MS can play in drug development, with a particular emphasis on PPI modulators.

Real-Time Library Search Increases Cross-Link Identification Depth across All Levels of Sample Complexity.

Cross-linking mass spectrometry (XL-MS) is a universal tool for probing structural dynamics and protein-protein interactions in vitro and in vivo. Although cross-linked peptides are naturally less abundant than their unlinked counterparts, recent experimental advances improved cross-link identification by enriching the cross-linker-modified peptides chemically with the use of enrichable cross-linkers. However, mono-links (i.e., peptides modified with a hydrolyzed cross-linker) still hinder efficient cross-link identification since a large proportion of measurement time is spent on their MS2 acquisition. Currently, cross-links and mono-links cannot be separated by sample preparation techniques or chromatography because they are chemically almost identical. Here, we found that based on the intensity ratios of four diagnostic peaks when using PhoX/tBu-PhoX cross-linkers, cross-links and mono-links can be partially distinguished. Harnessing their characteristic intensity ratios for real-time library search (RTLS)-based triggering of high-resolution MS2 scans increased the number of cross-link identifications from both single protein samples and intact E. coli cells. Specifically, RTLS improves cross-link identification from unenriched samples and short gradients, emphasizing its advantages in high-throughput approaches and when instrument time or sample amount is limited.

An Unusual Aspartic Acid Cluster in the Reovirus Attachment Fiber σ1 Mediates Stability at Low pH and Preserves Trimeric Organization.

The reovirus attachment protein σ1 mediates cell attachment and receptor binding and is thought to undergo conformational changes during viral disassembly. σ1 is a trimeric filamentous protein with an α-helical coiled-coil tail, a triple-ß-spiral body, and a globular head. At the trimer interface, the head domain features an unusual and conserved aspartic acid cluster, which forms the only significant intratrimer interactions in the head and must be protonated to allow trimer formation. To define the role of pH on σ1 stability and conformation, we tested its domains over a wide range of pH values. We show that all domains of σ1 are remarkably thermostable, even at the low pH of the stomach. We determined the optimal pH for stability to be between pHs 5 and 6, a value close to the pH of the endosome and of the jejunum. The σ1 head is stable at acidic and neutral pH but detrimerizes at basic pH. When Asp345 in the aspartic acid cluster is mutated to asparagine (D345N), the σ1 head loses stability at low pH and is more prone to detrimerize. Although the D345N mutation does not affect σ1 binding affinity for the JAM-A receptor, the overall binding stoichiometry is reduced by one-third. The additional replacement of the neighboring His349 with alanine disrupts inner trimer surface interactions, leading to a less thermostable and monomeric σ1 D345N head that fails to bind the JAM-A receptor. When the body is expressed together with the head domain, the thermostability is restored and the stoichiometry of the binding to JAM-A receptor is preserved. Our results confirm a fundamental role of the aspartic acid cluster as a pH-dependent molecular switch controlling trimerization and enhancing thermostability of σ1, which represent essential requirements to accomplish reovirus infection and entry and might be common mechanisms among other enteric viruses. IMPORTANCE Enteric viruses withstand the highly acidic environment of the stomach during transmission, and many of them use low pH as a trigger for conformational changes associated with entry. For many nonenveloped viruses, the structural basis of these effects is not clear. We have investigated the stability of the reovirus attachment protein σ1 over a range of pHs and find it to be remarkably thermostable, especially at low pH. We identify a role for the aspartic acid cluster in maintaining σ1 thermostability, trimeric organization, and binding to JAM-A receptor especially at the gastric pH reovirus has to withstand while passing the stomach. The understanding of monomer-trimer dynamics within σ1 enhances our knowledge of reovirus entry and has implications for stability and transmission of other enteric viruses.

Optimized TMT-Based Quantitative Cross-Linking Mass Spectrometry Strategy for Large-Scale Interactomic Studies.

Cross-linking mass spectrometry (XL-MS) is a powerful method for the investigation of protein-protein interactions (PPI) from highly complex samples. XL-MS combined with tandem mass tag (TMT) labeling holds the promise of large-scale PPI quantification. However, a robust and efficient TMT-based XL-MS quantification method has not yet been established due to the lack of a benchmarking dataset and thorough evaluation of various MS parameters. To tackle these limitations, we generate a two-interactome dataset by spiking in TMT-labeled cross-linked Escherichia coli lysate into TMT-labeled cross-linked HEK293T lysate using a defined mixing scheme. Using this benchmarking dataset, we assess the efficacy of cross-link identification and accuracy of cross-link quantification using different MS acquisition strategies. For identification, we compare various MS2- and MS3-based XL-MS methods, and optimize stepped higher energy collisional dissociation (HCD) energies for TMT-labeled cross-links. We observed a need for notably higher fragmentation energies compared to unlabeled cross-links. For quantification, we assess the quantification accuracy and dispersion of MS2-, MS3-, and synchronous precursor selection-MS3-based methods. We show that a stepped HCD-MS2 method with stepped collision energies 36-42-48 provides a vast number of quantifiable cross-links with high quantification accuracy. This widely applicable method paves the way for multiplexed quantitative PPI characterization from complex biological systems.